An instance of the quadratic minimum spanning tree problem (QMSTP) is called linearizable if it can be rewritten as an instance of the linear minimum spanning tree problem in such a way that the objective function value is preserved at all feasible solutions. Previous work has shown that a sufficient condition for linearizability is that … Read more
We introduce a polyhedral framework for characterizing instances of quadratic combinatorial optimization programs (QCOPs) as being linearizable, meaning that the quadratic objective can be equivalently rewritten as linear in such a manner that preserves the objective function value at all feasible solutions. In particular, we show that an instance is linearizable if and only if … Read more
The quadratic assignment problem (QAP) is an extremely challenging NP-hard combinatorial optimization program. Due to its difficulty, a research emphasis has been to identify special cases that are polynomially solvable. Included within this emphasis are instances which are linearizable; that is, which can be rewritten as a linear assignment problem having the property that the … Read more